With the completion of the human genome project and recent advances in high throughput technologies, much of the ongoing effort is now to find all the functional elements on the sequence and to create computational tools to analyze and interpret the large volume of data available. This overwhelming amount of information together with the complexity of biological systems has created a need for in silico modeling and the development of model-driven systems biology. The reconstruction of the reaction networks that these components form allows for the formulation of in silico models. Investing on our success in modeling microbial cells using constraints-based approach, we intend to assess the scientific and computational feasibility of building the first genome-scale metabolic model for human cells. We will build two cell-specific metabolic models, test and characterize them, and define the issues associated with building multi-cellular metabolic models. Given the prevalence of metabolic involvement in human disease, this effort is both timely and of great significance. The integration of the sequence annotation, the association relationships for splice variants, data representation and computational issues will be addressed at the completion of this project. Success of this proposal would build the foundation for the development of a comprehensive model of human metabolism that would be extremely valuable for drug discovery and development efforts and has the potential to drive the process of therapeutic research.